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AN APPLICATION FOR EFFICIENCY MEASUREMENT OF DEPOSIT BANKS WITH WEIGHT RESTRICTED DATA ENVELOPMENT ANALYSIS

Yıl 2013, , 215 - 238, 01.05.2013
https://doi.org/10.11122/ijmeb.2013.9.19.473

Öz

Data envelopment analysis DEA is a linear programming based method that is used for relative efficiency of decision making units producing similar outputs by using similar inputs. As well as the basic DEA models, it is also possible to incorporate decision makers’ preferences and/or market data into analysis through the Assurance Region AR method which is based on setting limits on the input and output weights. In this study, the efficiency of deposit banks operating in Turkey had been measured by using both the unrestricted weight model and the AR restricted model for the years 2011 and 2012, and the results has been compared. It has been seen that the discriminatory power of weight restricted DEA model for discerning efficient and inefficient banks is greater and it also enables to include market data apart from the data related to the variables used in the analysis

Kaynakça

  • Akın, A., Kılıç, M., & Zaim, S. (2009 , June). Determinants of bank efficiency in Turkey: a two stage data envelopment analysis. 1. International Symposium on Sustainable Development. Sarajevo.
  • Allen, R., Athanassopoulos, A., Dyson, R. G., & Thanassoulis, E. (1997). Weights restrictions and value judgments in data envelopment analysis: Evolution, development and future directions. Annals of Operations Research, 73, 13-34.
  • Andersen, P., & Petersen, N. C. (1993). A procedure for ranking efficient units in data envelopment analysis. Management Science, 39, 1261-1264.
  • Bal, H., & Gölcükcü, A. (2002). Data envelopment analysis: An application to Turkish banking industry. Mathematical and Computational Applications, 7, 65-72.
  • Başar, M., & Başar, A. B. (2006, November). Assessment Of Turkısh Banks’ Performance By Usıng Data Envelopment Analysis. Advancing Business and Management in Knowledge-Based Society, Proceedings of the 7th International Conference of the Faculty of Management Koper, Congress Centre Bernandin, Portoroz, Slovenia.
  • Behdioğlu, S., & Özcan, G. (2009). Veri zarflama analizi ve bankacılık sektöründe bir uygulama. Süleyman Demirel Üniversitesi, İktisadi ve İdari Bilimler Fakültesi Dergisi, 14, 301-326.
  • Bektaş, H. (2013). Türk bankacılık sektöründe etkinlik analizi. Sosyoekonomi, 1, 278- 294.
  • Benston, G. J. (1965). Branch banking and economies of scale. The Journal of Finance, 20, 312-331.
  • Berger, A. N., & Humphrey, D. B. (1997). Efficiency of financial institutions: International survey and directions for future research. European Journal of Operational Research, 98, 175-212.
  • Budak, H. (2011). Veri zarflama analizi ve türk bankacılık sektöründe uygulaması. Marmara Üniversitesi Fen Bilimleri Dergisi, 23, 95-110.
  • Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2, 429-444.
  • Colwell, R. J., & Davis, E. P. (1992). Output and productivity in banking. The Scandinavian Journal of Economics, 94, 111-129.
  • Cooper, W. W., Seiford, L. M., & Tone, K. (2002). Data envelopment analysis: A comprehensive text with models, applications, references and DEA-Solver software. Dordrecht: Kluwer Academic Publishers.
  • Cooper, W. W., Seiford, L. M., & Tone, K. (2006). Introduction to data envelopment analysis and its uses with DEA-Solver software and references. USA: Springer.
  • Cooper, W. W., Seiford, L. M., & Zhu, Joe. (2011). Handbook on data envelopment analysis. NY: Springer.
  • Denizer, C. A., Dinc, M., & Tarimcilar, M. (2007). Financial liberalization and banking efficiency: evidence from Turkey. Journal of Productivity Analysis, 27, 177-195.
  • Eleren, A., & Özgür E. (2006). Türkiye'de yabancı sermayeli mevduat bankalarının veri zarflama yöntemi ile etkinlik analizlerinin yapılması. Afyon Kocatepe Üniversitesi, İktisadi ve İdari Bilimler Fakültesi Dergisi, 8, 53-76.
  • Er, B., & Uysal M. (2012). Türkiye'deki ticari bankalar ve katılım bankalarının karşılaştırmalı etkinlik analizi: 2005-2010 dönemi değerlendirmesi. Atatürk Üniversitesi İktisadi ve İdari Bilimler Dergisi, 26, 365-387.
  • Farrell, M. J. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society, 120, 253-290.
  • Favero, C. A., & Papi, L. (1995). Technical efficiency and scale efficiency in the Italian banking sector: a non-parametric approach. Applied Economics, 27, 385-395.
  • Haas, D. A., & Murphy, F. H. (2003). Compensating for non-homogeneity in decision- making units in data envelopment analysis. European Journal of Operational Research, 144, 530-544.
  • Koçyiğit, M. M. (2013). Mevduat bankalarının etkinliği ve hisse senedi getirileri arasındaki ilişki. Muhasebe ve Finansman Dergisi, 1, 73-88.
  • Kumar, S., & Gulati, R. (2008). An examination of technical, pure technical, and scale efficiencies in Indian public sector banks using data envelopment analysis. Eurasian Journal of Business and Economics,1, 33-69.
  • Kumar, S., & Gulati, R. (2010). Measuring efficiency, effectiveness and performance of Indian public sector banks. International Journal of Productivity and Performance Management, 59, 51-74.
  • Mercan, M., Reisman, A., Yolalan, R., & Emel, A. B. (2003). The effect of scale and mode of ownership on the financial performance of the Turkish banking sector: results of a DEA-based analysis. Socio-Economic Planning Sciences, 37, 185- 202.
  • Pastor, J. T., & Ruiz, J. L. (2007). Variables with negative values in DEA. In J. Zhu, W. D. Cook (Eds.). Modeling data irregularities and structural complexities in data envelopment analysis. USA: Springer.
  • Ramanathan, R. (2003). An introduction to data envelopment analysis a tool for performance measurement. New Delhi: Sage Publications.
  • Şakar, B. (2006). A study on efficiency and productivity of Turkish banks in Istanbul stock exchange using Malmquist DEA. Journal of American Academy of Business, 8, 145-155.
  • Sarkis, J. (1999). A methodological framework for evaluating environmentally conscious manufacturing programs. Computers and Industrial Engineering, 36, 793-810.
  • Sarkis, J. (2000). A comparative analysis of DEA as a discrete alternative multiple criteria decision tool. European Journal of Operational Research, 123, 543-557.
  • Sarkis, J. L. (2007). Preparing your data for DEA. In J. Zhu, W. D. Cook (Eds.), Modeling data irregularities and structural complexities in data envelopment analysis. USA: Springer.
  • Sealey, C. W. Jr., & Lindley, J. T. (1977). Inputs, outputs, and a theory of production and cost at depository financial institutions. Journal of Finance, 32, 1251-1266.
  • Sherman, H. D., & Gold, F. (1985). Bank branch operating efficiency: Evaluation with data envelopment analysis. Journal of Banking and Finance, 9, 297-315.
  • Tarkoçin, C., & Gençer, M. (2010). Farklı girdi ve çıktı yaklaşımlarının veri zarflama analizi etkinlik sonuçlarına etkisi ve Türk ticari bankaları uygulaması. Bankacılar Dergisi, 72, 19-32.
  • Taylor, W. M., Thompson, R. G., Thrall, R. M., & Dharmapala, P. S. (1997). DEA/AR efficiency and profitability of Mexican banks A total income model. European Journal of Operational Research, 98, 346-363.
  • Thompson, R. G., Brinkmann, E. J., Dharmapala, P. S., Gonzalez-Lima, M. D., & Thrall, R. M. (1997). DEA/AR profit ratios and sensitivity of 100 large U.S. banks. European Journal of Operational Research, 98, 213-229.
  • Thompson, R. G., Dharmapala, P. S., Humphrey, D. B., Taylor, W. M., & Thrall, R. M. (1996). Computing DEA/AR efficiency and profit ratio measures with an illustrative bank application. Annals of Operations Research, 68, 303-327.
  • Thompson, R. G., Singleton Jr, F. D., Thrall, R. M., & Smith, B. A. (1986). Comparative site evaluations for locating a High-Energy Physics Lab in Texas. Interfaces, 16, 35-49.
  • Türkiye Bankalar Birliği. (2011, 2012). Bankalarımız. Erişim Tarihi: 30.05.2013, www.tbb.org.tr.
  • Türkiye Cumhuriyet Merkez Bankası. Faiz İstatistikleri. Erişim Tarihi: 01.06.2013, http://evds.tcmb.gov.tr/cbt.html.
  • Zhu, J. (2009). Quantitative models for performance evaluation and benchmarking data envelopment analysis with spreadsheets. Second Edition, USA: Springer.

AĞIRLIK KISITLI VERİ ZARFLAMA ANALİZİ İLE MEVDUAT BANKALARININ ETKİNLİK ÖLÇÜMÜNE YÖNELİK BİR UYGULAMA

Yıl 2013, , 215 - 238, 01.05.2013
https://doi.org/10.11122/ijmeb.2013.9.19.473

Öz

Veri Zarflama Analizi VZA benzer girdiler kullanarak benzer çıktılar üreten karar verme birimlerinin göreli etkin ölçümünde kullanılan ve doğrusal programlama tabanlı bir yöntemdir. Temel VZA modellerinin yanı sıra girdi ve çıktı değişkenlerinin ağırlıklarına sınırlar konmasına dayanan Güven Bölgesi AR yöntemiyle de karar vericilerin tercihleri ve/veya piyasa verileri de analize dahil edilebilmektedir. Çalışmada Türkiye’de faaliyet gösteren mevduat bankalarının 2011 ve 2012 yılları için etkinlikleri hem ağırlık kısıtsız hem de AR kısıtlı model kullanılarak ölçülmüş ve sonuçlar karşılaştırılmıştır. Ağırlık kısıtlı VZA modelinin etkin olan ve olmayan bankaları ayrıştırma gücünün daha yüksek olduğu ayrıca modelde kullanılan değişkenlerin verileri dışındaki piyasa verilerinin de analize dahil edilmesine imkan sağladığı görülmektedir.

Kaynakça

  • Akın, A., Kılıç, M., & Zaim, S. (2009 , June). Determinants of bank efficiency in Turkey: a two stage data envelopment analysis. 1. International Symposium on Sustainable Development. Sarajevo.
  • Allen, R., Athanassopoulos, A., Dyson, R. G., & Thanassoulis, E. (1997). Weights restrictions and value judgments in data envelopment analysis: Evolution, development and future directions. Annals of Operations Research, 73, 13-34.
  • Andersen, P., & Petersen, N. C. (1993). A procedure for ranking efficient units in data envelopment analysis. Management Science, 39, 1261-1264.
  • Bal, H., & Gölcükcü, A. (2002). Data envelopment analysis: An application to Turkish banking industry. Mathematical and Computational Applications, 7, 65-72.
  • Başar, M., & Başar, A. B. (2006, November). Assessment Of Turkısh Banks’ Performance By Usıng Data Envelopment Analysis. Advancing Business and Management in Knowledge-Based Society, Proceedings of the 7th International Conference of the Faculty of Management Koper, Congress Centre Bernandin, Portoroz, Slovenia.
  • Behdioğlu, S., & Özcan, G. (2009). Veri zarflama analizi ve bankacılık sektöründe bir uygulama. Süleyman Demirel Üniversitesi, İktisadi ve İdari Bilimler Fakültesi Dergisi, 14, 301-326.
  • Bektaş, H. (2013). Türk bankacılık sektöründe etkinlik analizi. Sosyoekonomi, 1, 278- 294.
  • Benston, G. J. (1965). Branch banking and economies of scale. The Journal of Finance, 20, 312-331.
  • Berger, A. N., & Humphrey, D. B. (1997). Efficiency of financial institutions: International survey and directions for future research. European Journal of Operational Research, 98, 175-212.
  • Budak, H. (2011). Veri zarflama analizi ve türk bankacılık sektöründe uygulaması. Marmara Üniversitesi Fen Bilimleri Dergisi, 23, 95-110.
  • Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2, 429-444.
  • Colwell, R. J., & Davis, E. P. (1992). Output and productivity in banking. The Scandinavian Journal of Economics, 94, 111-129.
  • Cooper, W. W., Seiford, L. M., & Tone, K. (2002). Data envelopment analysis: A comprehensive text with models, applications, references and DEA-Solver software. Dordrecht: Kluwer Academic Publishers.
  • Cooper, W. W., Seiford, L. M., & Tone, K. (2006). Introduction to data envelopment analysis and its uses with DEA-Solver software and references. USA: Springer.
  • Cooper, W. W., Seiford, L. M., & Zhu, Joe. (2011). Handbook on data envelopment analysis. NY: Springer.
  • Denizer, C. A., Dinc, M., & Tarimcilar, M. (2007). Financial liberalization and banking efficiency: evidence from Turkey. Journal of Productivity Analysis, 27, 177-195.
  • Eleren, A., & Özgür E. (2006). Türkiye'de yabancı sermayeli mevduat bankalarının veri zarflama yöntemi ile etkinlik analizlerinin yapılması. Afyon Kocatepe Üniversitesi, İktisadi ve İdari Bilimler Fakültesi Dergisi, 8, 53-76.
  • Er, B., & Uysal M. (2012). Türkiye'deki ticari bankalar ve katılım bankalarının karşılaştırmalı etkinlik analizi: 2005-2010 dönemi değerlendirmesi. Atatürk Üniversitesi İktisadi ve İdari Bilimler Dergisi, 26, 365-387.
  • Farrell, M. J. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society, 120, 253-290.
  • Favero, C. A., & Papi, L. (1995). Technical efficiency and scale efficiency in the Italian banking sector: a non-parametric approach. Applied Economics, 27, 385-395.
  • Haas, D. A., & Murphy, F. H. (2003). Compensating for non-homogeneity in decision- making units in data envelopment analysis. European Journal of Operational Research, 144, 530-544.
  • Koçyiğit, M. M. (2013). Mevduat bankalarının etkinliği ve hisse senedi getirileri arasındaki ilişki. Muhasebe ve Finansman Dergisi, 1, 73-88.
  • Kumar, S., & Gulati, R. (2008). An examination of technical, pure technical, and scale efficiencies in Indian public sector banks using data envelopment analysis. Eurasian Journal of Business and Economics,1, 33-69.
  • Kumar, S., & Gulati, R. (2010). Measuring efficiency, effectiveness and performance of Indian public sector banks. International Journal of Productivity and Performance Management, 59, 51-74.
  • Mercan, M., Reisman, A., Yolalan, R., & Emel, A. B. (2003). The effect of scale and mode of ownership on the financial performance of the Turkish banking sector: results of a DEA-based analysis. Socio-Economic Planning Sciences, 37, 185- 202.
  • Pastor, J. T., & Ruiz, J. L. (2007). Variables with negative values in DEA. In J. Zhu, W. D. Cook (Eds.). Modeling data irregularities and structural complexities in data envelopment analysis. USA: Springer.
  • Ramanathan, R. (2003). An introduction to data envelopment analysis a tool for performance measurement. New Delhi: Sage Publications.
  • Şakar, B. (2006). A study on efficiency and productivity of Turkish banks in Istanbul stock exchange using Malmquist DEA. Journal of American Academy of Business, 8, 145-155.
  • Sarkis, J. (1999). A methodological framework for evaluating environmentally conscious manufacturing programs. Computers and Industrial Engineering, 36, 793-810.
  • Sarkis, J. (2000). A comparative analysis of DEA as a discrete alternative multiple criteria decision tool. European Journal of Operational Research, 123, 543-557.
  • Sarkis, J. L. (2007). Preparing your data for DEA. In J. Zhu, W. D. Cook (Eds.), Modeling data irregularities and structural complexities in data envelopment analysis. USA: Springer.
  • Sealey, C. W. Jr., & Lindley, J. T. (1977). Inputs, outputs, and a theory of production and cost at depository financial institutions. Journal of Finance, 32, 1251-1266.
  • Sherman, H. D., & Gold, F. (1985). Bank branch operating efficiency: Evaluation with data envelopment analysis. Journal of Banking and Finance, 9, 297-315.
  • Tarkoçin, C., & Gençer, M. (2010). Farklı girdi ve çıktı yaklaşımlarının veri zarflama analizi etkinlik sonuçlarına etkisi ve Türk ticari bankaları uygulaması. Bankacılar Dergisi, 72, 19-32.
  • Taylor, W. M., Thompson, R. G., Thrall, R. M., & Dharmapala, P. S. (1997). DEA/AR efficiency and profitability of Mexican banks A total income model. European Journal of Operational Research, 98, 346-363.
  • Thompson, R. G., Brinkmann, E. J., Dharmapala, P. S., Gonzalez-Lima, M. D., & Thrall, R. M. (1997). DEA/AR profit ratios and sensitivity of 100 large U.S. banks. European Journal of Operational Research, 98, 213-229.
  • Thompson, R. G., Dharmapala, P. S., Humphrey, D. B., Taylor, W. M., & Thrall, R. M. (1996). Computing DEA/AR efficiency and profit ratio measures with an illustrative bank application. Annals of Operations Research, 68, 303-327.
  • Thompson, R. G., Singleton Jr, F. D., Thrall, R. M., & Smith, B. A. (1986). Comparative site evaluations for locating a High-Energy Physics Lab in Texas. Interfaces, 16, 35-49.
  • Türkiye Bankalar Birliği. (2011, 2012). Bankalarımız. Erişim Tarihi: 30.05.2013, www.tbb.org.tr.
  • Türkiye Cumhuriyet Merkez Bankası. Faiz İstatistikleri. Erişim Tarihi: 01.06.2013, http://evds.tcmb.gov.tr/cbt.html.
  • Zhu, J. (2009). Quantitative models for performance evaluation and benchmarking data envelopment analysis with spreadsheets. Second Edition, USA: Springer.
Toplam 41 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Bölüm Research Article
Yazarlar

Aslı Özdemir Bu kişi benim

Erhan Demireli Bu kişi benim

Yayımlanma Tarihi 1 Mayıs 2013
Yayımlandığı Sayı Yıl 2013

Kaynak Göster

APA Özdemir, A., & Demireli, E. (2013). AĞIRLIK KISITLI VERİ ZARFLAMA ANALİZİ İLE MEVDUAT BANKALARININ ETKİNLİK ÖLÇÜMÜNE YÖNELİK BİR UYGULAMA. Uluslararası Yönetim İktisat Ve İşletme Dergisi, 9(19), 215-238. https://doi.org/10.11122/ijmeb.2013.9.19.473